Lead Computer Vision Engineer

2 weeks ago

United Kingdom CellVoyant Full time

CellVoyant is a biotechnology company that predicts stem cell differentiation using live cell microscopy and artificial intelligence. We use this approach to optimise and unlock human tissue manufacturing for research and therapeutics applications.

We spun out from the Carazo Salas lab at the University of Bristol in 2022 and are backed by venture capital firms who were the earliest investors in DeepMind, Exscientia, Recursion, Wayve, and Abcam.

What we’re looking for

As Lead Computer Vision Engineer, you are responsible for the design, build and continuous improvement of the computer vision systems that power our core cell fate prediction platform.

You’ll be working closely with the Software team (who build our infrastructure and internal applications) and Biology team (who design and run our cell biology experiments for microscopy data collection and differentiation protocol development).

You will build, integrate, test and scale computer vision models that make cell fate predictions using live cell microscopy data generated by the Biology team.

What you’ll do in this role
  • Provide technical leadership and implement machine learning engineering best practices, including defining the vision and AI strategy at CellVoyant in collaboration with the leadership team.
  • Communicate and drive consensus on this strategy and plan with other teams across the company.
  • Create production-grade machine learning systems using state-of-the-art research in stem cell fate prediction and label-free microscopy.
  • Define and build our internal training, testing, and serving infrastructure in collaboration with the Software team.
  • Collaborate with our Biology team to design and implement new neural network architectures for cell tracking and fate prediction using high-resolution microscopy data.
Our ideal candidate will have
  • 5+ years machine learning engineering experience with full lifecycle development from research, design and inception to production of ML applications.
  • Past experience managing a team of machine learning engineers.
  • Passion to take research ideas into production.
  • Experience with modern ML frameworks (past experience with PyTorch preferred).
  • Expertise with cloud infrastructure, distributed systems, and MLOps.
  • Experience with continuous integration systems, testing and metrics for deep learning features/models.
  • High standards for clear, actionable communication of data-driven processes.
  • Stay informed on the latest research in relevant scientific fields and analyze its potential impact on our capabilities.
  • BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience.
Nice to haves
  • Experience in a biotechnology company or a background in biology are  not necessary, but intellectual curiosity is a must
  • Experience working on AI-first software products, data platforms, and machine learning infrastructure tools, and bonus if in the context of biotechnology.
What we offer at CellVoyant
  • Join at the ground level to work at the cutting-edge of artificial intelligence, stem cell biology, empirical experiment automation, and cell therapy development.
  • An inclusive, collaborative and intellectually stimulating culture that puts science at the forefront of everything we do.
  • A dynamic, diverse, and inclusive team of experienced and interdisciplinary scientists applying their skills to some of the most impactful problems in human health.
  • Competitive salary and founding equity compensation.
  • Ability to work remotely or in our Bristol, UK headquarters and join bi-annual week-long company off sites.
The interview process:
  • Initial phone screen (30 mins)
  • At-home technical test
  • Technical interview reviewing the test results and follow-up (90 mins)
  • Meet the Team (onsite including tour 60 mins)
How to Apply

Does this role sound like a good fit? Email us at careers@cellvoyant.com including the role’s title in the subject line with your CV or personal website where we can learn about your experience.

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